How to Implement an Adaptive Rate Limiter in Python

import time
import random

class AdaptiveRateLimiter:
    """Simple adaptive rate limiter that reduces requests when error rate is high."""
    
    def __init__(self, min_interval=0.1, max_interval=2.0, error_threshold=0.3):
        self.min_interval = min_interval
        self.max_interval = max_interval
        self.error_threshold = error_threshold
        self.interval = min_interval
        self._last_time = 0.0
        self._recent_errors = []
        self._window_size = 10
        
    def _error_rate(self):
        if not self._recent_errors:
            return 0.0
        return sum(self._recent_errors) / len(self._recent_errors)
    
    def _adjust(self):
        rate = self._error_rate()
        if rate > self.error_threshold:
            self.interval = min(self.interval * 1.5, self.max_interval)
        elif rate < self.error_threshold / 2:
            self.interval = max(self.interval / 1.5, self.min_interval)
    
    def call(self, success):
        now = time.monotonic()
        wait = max(0.0, self._last_time + self.interval - now)
        if wait > 0:
            time.sleep(wait)
        self._last_time = time.monotonic()
        
        self._recent_errors.append(0 if success else 1)
        if len(self._recent_errors) > self._window_size:
            self._recent_errors.pop(0)
        self._adjust()
        return self.interval

def mock_api():
    """Mock API with ~40% failure rate."""
    return random.random() > 0.4

if __name__ == "__main__":
    limiter = AdaptiveRateLimiter()
    print(f"Initial interval: {limiter.interval:.3f}s")
    for _ in range(30):
        interval = limiter.call(mock_api())
        if _ % 5 == 4:
            print(f"Step {_+1:2d} | interval: {interval:.3f}s | error rate: {limiter._error_rate():.2f}")